I don’t disagree with you but most of the energy that people complain about AI using is used to train the models, not use them. Once they are trained it is fast to get what you need out of it, but making the next version takes a long time.
Once a model has been trained once they don’t just stop training. They refine and/or start training new models. Showing demand for these models is what has encouraged construction on 100s of new datacenters.
Only because of brute force over efficient approaches.
Again, look up Deepseek’s FP8/multi GPU training paper, and some of the code they published. They used a microscopic fraction of what OpenAI or X AI are using.
And models like SDXL or Flux are not that expensive to train.
It doesn’t have to be this way, but they can get away with it because being rich covers up internal dysfunction/isolation/whatever. Chinese trainers, and other GPU constrained ones, are forced to be thrifty.
And I guess they need it to be inefficient and expensive, so that it remains exclusive to them. That’s why they were throwing a tantrum at Deepseek, because they proved it doesn’t have to be.
Altman et al want to kill open source AI for a monopoly.
This is what the entire AI research space already knew even before deepseek hit, and why they (largely) think so little of Sam Altman.
The real battle in the space is not AI vs no AI, but exclusive use by AI Bros vs. open models that bankrupt them. Which is what I keep trying to tell /c/fuck_ai, as the “no AI” stance plays right into the AI Bro’s hands.
I don’t disagree with you but most of the energy that people complain about AI using is used to train the models, not use them. Once they are trained it is fast to get what you need out of it, but making the next version takes a long time.
This is a specious argument.
Once a model has been trained once they don’t just stop training. They refine and/or start training new models. Showing demand for these models is what has encouraged construction on 100s of new datacenters.
Only because of brute force over efficient approaches.
Again, look up Deepseek’s FP8/multi GPU training paper, and some of the code they published. They used a microscopic fraction of what OpenAI or X AI are using.
And models like SDXL or Flux are not that expensive to train.
It doesn’t have to be this way, but they can get away with it because being rich covers up internal dysfunction/isolation/whatever. Chinese trainers, and other GPU constrained ones, are forced to be thrifty.
And I guess they need it to be inefficient and expensive, so that it remains exclusive to them. That’s why they were throwing a tantrum at Deepseek, because they proved it doesn’t have to be.
Bingo.
Altman et al want to kill open source AI for a monopoly.
This is what the entire AI research space already knew even before deepseek hit, and why they (largely) think so little of Sam Altman.
The real battle in the space is not AI vs no AI, but exclusive use by AI Bros vs. open models that bankrupt them. Which is what I keep trying to tell /c/fuck_ai, as the “no AI” stance plays right into the AI Bro’s hands.
that’s absolutely not true. In fact, most people who complain don’t even know the difference.